What this book covers

Chapter 1, Why GCP?, this chapter introduces readers to the Google Cloud Platform. It provides an overview of cloud computing, a brief history of GCP, as well as a comparison to other public cloud providers.

Chapter 2, The Google Cloud Console, this chapter serves to familiarize readers with the primary user interfaces they will use when interacting with Google Cloud.

Chapter 3, APIs, CLIs, IAM, and Billing, in this chapter, readers will learn about the various command line tools provided by Google for managing cloud resources. Readers will also learn about the other tools that will enable them to manage their Google Cloud projects throughout the book.

Chapter 4, Google App Engine, this chapter will explain what Google App Engine (GAE) is, the driving philosophies behind it, and how to use it to run highly-scalable services.

Chapter 5, Google Kubernetes Engine, this chapter is about the Google Container Engine (GKE) platform for running and managing services on Google Cloud.

Chapter 6, Google Cloud Functions, this chapter is about creating and executing Cloud Functions using Google's serverless platform.

Chapter 7, Google Compute Engine, this chapter is about Google's IaaS offering: Google Compute Engine (GCE). This chapter will introduce readers to on-demand VMs and how they can be managed, scaled, and customized to the user's needs.

Chapter 8, NoSQL with Datastore and Bigtable, this chapter will introduce readers to the document based storage solutions offered by Google, including Datastore (plus the new Firestore), and Bigtable.

Chapter 9, Relational Data with Cloud SQL and Cloud Spanner, this chapter will cover Google's relational data storage solutions, including managed MySQL and PostgreSQL via Cloud SQL, as well as globally consistent relational data via Cloud Spanner.

Chapter 10, Google Cloud Storage, this chapter is about Google's unified object storage platform: Google Cloud Storage (GCS).

Chapter 11, Stackdriver, this chapter will cover Google's Stackdriver monitoring, logging, and diagnostics suite to drive application insights, availability, and fast incident resolution.

Chapter 12, Change Management, this chapter will introduce readers to the various platform tools Google offers around the developer/operations experience, including source control, building and deploying services.

Chapter 13, GCP Networking for Developers, this chapter will introduce readers to networking on Google Cloud, covering the products available and how to use them to build custom networking and security solutions. These topics will be presented in a manner appropriate for developers rather than networking professionals.

Chapter 14, Messaging with Pub/Sub and IoT Core, this chapter will introduce readers to the distributed messaging offerings on Google Cloud. Readers will learn how to leverage Google Cloud Pub/Sub for high-throughput messaging used both in service to service communications and Big Data ingestion pipelines, as well as Cloud IoT Core for widely distributed event-driven application architectures.

Chapter 15, Integrating with Big Data Solutions on GCP, this chapter will provide a high-level overview of big data solutions on the Google Cloud Platform. Users will learn how to build highly scalable, fully managed big data solutions with the power of Cloud Dataflow and BigQuery.

Chapter 16, Compute, contains recipes on the compute services of the GCP, namely Google Compute Engine, Google App Engine, Kubernetes Engine, and Google Cloud Functions.

Chapter 17, Storage and Databases, provides some recipes on Google Cloud Storage and some of the database options available (Cloud Spanner, Cloud BigQuery, Cloud Bigtable, and Cloud Datastore).

Chapter 18, Networking, provides a few advanced recipes on connecting two networks and
handling traffic to websites

Chapter 19, Security, discusses how to use some out-of-the-box security tools provided by the GCP and how GCP provides APIs to set up your own security systems.

Chapter 20, Machine Learning and Big Data, contains a few recipes that show the breadth of the big data offerings of GCP and some applied machine learning APIs, which will be directly consumed for our needs.

Chapter 21, Management Tools, shows us some recipes on the Stackdriver suite and the logging system to help us manage our Cloud Platform.

Chapter 22, Best Practices, covers some third-party tools and processes that can be used at the enterprise scale to derive the maximum benefit from the GCP.